Laurence T. Maloney

Cognition & Perception, Center for Neural Science, Center for Brain Imaging, Center for Experimental Social Science

Complete CV (PDF Format)

Research

Visual perception, decision making and movement planning.
I am interested in how organisms gather information and act on it. My laboratory supports six main lines of research.
You can click on any of the pictures below to find out more.

surface color in 3D scenes movement planning under risk material perception
statistical models of visual judgement geometric models of visual judgments face perception

Biography

Education

B.A, 1973, Yale University, Mathematics
M.S., 1982, Stanford University, Statistics
Ph.D., 1985, Stanford University, Psychology

In college, at Yale, I majored in mathematics with occasional courses in computer science and automata theory. After graduation, I spent six years as a systems programmer designing operating systems for computers and, then entered the doctoral program in Psychology at Stanford. While I was there I was also able to take graduate courses in statistics in several departments, leading to an M.S. in Mathematical Statistics and a minor in Electrical Engineering.

At Stanford I studied color vision with Brian Wandell, issues of representation and measurement with Amos Tversky, and signal detection theory and statistical modeling with Ewart A. C. Thomas. My doctoral dissertation concerned surface color perception and color constancy. After a brief stay as an Associate at NASA-Ames, I spent three years at the University of Michigan, Ann Arbor as an assistant professor and then moved to join the vision group at New York University, where I remain.

My central research interest is the comparison of human performance to models of performance based on mathematical statistics, physics and mathematics.


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Awards [partial list]

    • Humboldt Research Award of the Alexander von Humboldt Foundation, Germany, 2008
    • Troland Research Award of the National Academy of Sciences, 1987.
    • Fellow, American Association for the Advancement of Science, selected 2012.
    • Fellow, Society for Experimental Psychology, elected 2009.
    • Fellow, Association for Psychological Science, elected 2011.
    • Fellow, Zentrum für interdisziplinäre Forschung, Bielefeld, Germany, 1995-96.
    • Forchheimer Professor, Computer Science, Hebrew University, Jerusalem, 1999.
    • WICN Visiting Scholar, Wales Institute of Cognitive Neuroscience, Bangor University, Bangor, Wales, 2008.
    • Golden Dozen Teaching Award, New York University, 1994.

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Publications

Recent Publications

2012 and in press

Knoblauch, K. & Maloney, L. T. (2012), Modeling Psychophysical Data in R. New York: Springer.

Zhang, H., Morvan, C., Etezad-Heydari, L.-A.,Maloney, L. T. (2012), Very slow search and reach: eye-hand coordination in finding and touching a target among distractors. PLoS Computational Biology, 8(10): e1002718. doi:10.1371/journal.pcbi.1002718, 1-12. [pdf]

Hudson, T. E., Wolfe, U. &Maloney, L. T.(2012),Speeded reaching movements around invisible obstacles. PLoS Computational Biology, 8(9): e1002676. doi:10.1371/journal.pcbi.1002676, 1-9. [pdf]

Charrier, C., Knoblauch, K., Maloney, L. T.,  Bovik, A. C. & Morthy, A.  (2012), Optimizing multi-scale SSIM via MLDS. IEEE: Transactions on Image Processing, 21 (12), 4682-4694. [pdf]

Juni, M.,Gureckis, T. M. &Maloney, L. T. (2012),Effective integration of serially presented stochastic cues.  Journal of Vision, 12(8):12, 1-16. [article]

Glaser, C. Trommershäuser, J., Mamassian, P. & Maloney, L. T. (2012), Comparison of the distortion of probability information in decision under risk and in an equivalent visual task. Psychological Science, 23(4), 419-426. [pdf]

Warren, P. A., Graf, E. W., Champion, R. & Maloney, L. T. (2012), Extrapolation under risk: human observers estimate and compensate for exogeneous uncertainty. Proceedings of the Royal Society, Series B, 279(1736), 2171-2179. [pdf]

Zhang, H. & Maloney, L.T. (2012), Ubiquitous log odds: a common representation for probability and requency distortion in perception, action and cognition. Frontiers in Neuroscience, 6 (1), 1-14. [pdf]

Morvan, C. & Maloney, L. T. (2012), Human visual search does not maximize the post-saccadic probability of identifying targets. PLoS Computational Biology, 8(2), e1002342, 1-11. [pdf]

Juni, M. Z., Gureckis, T. M. & Maloney, L. T. (2012) One-shot lotteries in the park. In N. Miyake, Peebles, D. & Cooper, R.P. (Eds.) Proceedings of the 34th Annual Conference of the Cognitive Science Society, in press. Austin, TX: Cognitive Science Society. [pdf]

2011

Wu, S.-W., Delgado, M. R. & Maloney, L. T. (2011), The neural correlates of subjective utility of monetary outcome and probability weight in economic and in motor decision under risk. Journal of Neuroscience, 31, 8822-8831. [pdf]

Brainard, D. H. & Maloney, L. T. (2011), Surface color perception and equivalent illumination models. Journal of Vision, 11(5):1, 1–18 [pdf]

Fujikake, H., Higuchi, T., Imanaka, K., & Maloney, L. T. (2011), Directional bias in the body while walking through a doorway: Its association with motor and cognitive factors. Experimental Brain Research, 210, :195–206. [pdf]

Fleming, R. W., Jäkel, F., Maloney, L. T. (2011) Visual perception of transparent materials. Psychological Science, in press, 22(6), 812-820. [pdf]

Juni, M. Z., Gureckis, T. M. & Maloney, L. T. (2011), Don't Stop 'Til You Get Enough: Adaptive Information Sampling in a Visuomotor Estimation Task" in L. Carlson, C. Hölscher and T. Shipley (Eds), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 2854-2859). Austin, TX: Cognitive Science Society. [pdf]

Charrier, C., Knoblauch, K., Maloney, L. T., & Bovik, A. C. (2011), Calibrating MS-SSIM for compression distortions using MLDS. 18th IEEE International Conference on Image Processing (ICIP 2011), accepted 4/17/2011. [pdf]

Maloney, L. T., Gerhard, H. E., Boyaci, H. & Doerschner, K.  (2011), Surface color perception and light field estimation in 3D scenes.  In Harris, L. R. & Jenkin, M. R. M. [Eds], Vision in 3D environments.  Cambridge, UK: Cambridge University Press, pp. 280-307. [pdf]


2010

Zhang, H., Maddula, S. & Maloney, L.T. (2010), Planning routes across economic terrains: maximizing utility, following heuristics. Frontiers in Psychology, 1, 1-10. [pdf

Juni, M. Z., Singh, M. & Maloney, L. T. (2010), Robust visual estimation as source separation. Journal of Vision, 10(14):2, 1-20. [Article

Zhang, H., Morvan, C. & Maloney, L. T.  (2010), Gambling in the visual periphery: a conjoint-measurement analysis of human ability to judge visual uncertainty.   PLoS Computational Biology, 6(12): e1001023, 1-10. [pdf

Maloney, L. T. & Zhang, H. (2010), Decision-theoretic models of visual perception and action. Vision Research, 50, 2362-2374. [pdf

Doerschner, K., Maloney, L. T.  & Boyaci, H. (2010), Perceived glossiness in high dynamic range scenes. Journal of Vision, 10(9):11, 1-11. [Article]  

Gerhard, H. E. & Maloney, L. T. (2010) Estimating changes in lighting direction in binocularly-viewed three-dimensional scenes. Journal of Vision, 10(9):14, 1-22. [Article]

Dal Martello, M. F. & Maloney, L. T. (2010),Lateralization of kin recognition signals in the human face. Journal of Vision, 10(8):9, 1-10. [article]

Gerhard, H. E. & Maloney, L. T. (2010) Detection of light transformations and concomitant changes in surface albedo. Journal of Vision, 10(9):1,  1-14. [article]

Zhang, H., Wu, S.-W. & Maloney, L. T. (2010), Planning multiple movements within a fixed time limit: The cost of active time allocation in a visuo-motor task. Journal of Vision, 10(6):1, 1-17. [article]

Emrith, K., Chantler, M. J., Green, P. R., Maloney, L. T. & Clarke, A. D. F. (2010), Measuring perceived differences in surface texture due to changes in higher order statistics, Journal of the Optical Society of America A, 27(5), 1232-1244. Included in Virtual Journal for Biomedical Optics, 5(9), July 6, 2010. [pdf]

Doerschner, K., Boyaci, H. & Maloney, L. T. (2010), Estimating the glossiness transfer function induced by illumination change and testing its transitivity. Journal of Vision, 10(4):8, 1-9. [article]

Kwon, O. S., Gerhard, H. E. & Maloney, L. T. (2010), Surface reflectance models based on characteristic functions. CGIV'2010, in press, 2/2010.

Maloney, L. T., Gerhard, H. E., Boyaci, H. & Doerschner, K. (2010), Surface color perception and light field estimation in 3D scenes. In Harris, L. & Jenkins, M. [Eds], Vision in 3D environments. Cambridge, UK: Cambridge University Press, pp. 65-88. [pdf]

Charrier, C., Knoblauch, K., Morthy, A. Bovik, A. C. & Maloney, L. T. (2010), On the comparison of image quality assessment algorithms, Electronic Imaging '10: Image quality and system performance. San Jose, CA, January, 2010, IS &T/SPIE Paper Number 7529-10. [pdf]

2009

Wu, S.-W., Dal Martello, M. F. & Maloney, L. T. (2009), Sub-optimal tradeoff of time in sequential movements. PLoS ONE, 4(12): e8228, 1-13. [pdf]

Ho, Y.-X., Serwe, S., Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2009), The role of visuo-haptic experience in visually perceived depth. Journal of Neurophysiology, 101(6), 2789-2801. [pdf]

Wu, S.-W., Delgado, M. & Maloney, L. T. (2009), Economic decision-making compared to an equivalent motor task, Proceedings of the National Academy of Sciences, USA, 106(15), 6088-6093. [pdf]

Glanzer, M., Hilford, A. & Maloney, L. T. (2009), Likelihood ratio decisions in memory: Three implications. Psychonomic Bulletin & Review, 16(3), 431-455. [pdf]

Fulvio, J. M., Singh, M. & Maloney, L. T. (2009), An experimental criterion for consistency in the interpolation of partially-occluded contours. Journal of Vision, 9(4):5, 1-19. [article]

Maloney, L. T. & Mamassian, P. (2009), Bayesian decision theory as a model of visual perception: Testing Bayesian transfer. Visual Neuroscience, 26, 147-155. [pdf]

Maloney, L. T. (2009), Perceptual-motor integration. In Goldstein, E. B. [Ed], Encyclopedia of Perception, Sage Publications, in press, 2/2009.

Maloney, L. T. (2009), Surface material properties perception. In Goldstein, E. B. [Ed], Encyclopedia of Perception, Sage Publications, in press, 1/2009.

Maloney, L. T. (2009), Book review: Introduction to probability with R by Kenneth Baclawski, Journal of Statistical Software, 30:BR1, 1-3. [pdf]


2008

Knoblauch, K. & Maloney, L. T. (2009), Estimating classification images with generalized additive models. Journal of Vision, 8(16):10, 1-19, [article]

Kitazaki, M., Kobiki, H. & Maloney, L.T. (2008), The effect of pictorial depth cues, binocular disparity and motion parallax depth cues on lightness perception in three-dimensional virtual scenes, PLoS ONE, 3(9): e3177, 1-9. [pdf]

Hudson, T. E., Maloney, L. T. & Landy, M. S. (2008), Optimal compensation for temporal uncertainty in movement planning. PLoS Computational Biology, 4(7):e100130, 1-9. [pdf]

Trommershäuser, J., Maloney, L. T. & Landy M. S. (2008), Decision making, movement planning and statistical decision theory. Trends in Cognitive Science, 12(8), 291-297 [pdf]

Ho, Y.-H., Landy. M. S. & Maloney, L. T. (2008), Conjoint measurement of gloss and surface texture. Psychological Science, 19(2), 196-204. [pdf]

Yeshurun, Y., Carrasco, M. & Maloney, L. T. (2008), Bias and sensitivity in two-interval forced-choice procedures, Vision Research, 48, 1837-1851 [pdf]

Gepshtein, S., Elder, J. & Maloney, L. T. (2008), Perceptual organization and neural computation, Journal of Vision, 8(7):i, 1-4. [pdf]

Fulvio, J. M., Singh, M. & Maloney, L. T. (2008), Precision and consistency of contour interpolation, Vision Research , 48(6), 831-849 [pdf]

Tokunaga, R., Logvinenko, A. D. & Maloney, L. T. (2008), Multidimensional scaling of dissimilarities between yellow-blue surfaces rated under neutral light sources. Visual Neuroscience, 25, 395-398 [pdf]

Knoblauch, K. & Maloney, L. T. (2008), MLDS: Maximum likelihood difference scaling in R. Journal of Statistical Software, 25(2), 1-26.[pdf]

Cohen, E. H., Singh, M. & Maloney, L. T. (2008), Perceptual segmentation and the perceived orientation of dot clusters: The role of robust statistics. Journal of Vision, 8(7), 1-13 [pdf]

Logvinenko, A., Petrini, K. & Maloney, L. T. (2008), A scaling analysis of the snake lightness illusion. Perception & Psychophysics, 70(5), 828-840 [pdf]

Trommershäuser, J., Maloney, L. T. & Landy M. S. (2008), The expected utility of movement. In Glimcher, P., Camerer, C., Fehr, E & Poldrack, R. (Eds), Neuroeconomics, New York: Academic Press, pp. 95-111. [pdf]

2007

Hudson, T. E., Maloney, L. T. & Landy, M. S. (2007), Movement planning with probabilistic target information. Journal of Neurophysiology, 98, 3034-3046. [pdf]

Doerschner, K., Boyaci, H. & Maloney, L. T. (2007), Testing limits on matte surface color perception in three-dimensional scenes with complex light fields, Vision Research, 47, 3409-3423. [pdf]

Charrier, C., Maloney, L. T., Cherifi, H. & Knoblauch, K., (2007), Maximum likelihood difference scaling of image quality in compression-degraded images. Journal of the Optical Society of America A, 24, 3814-3826. [pdf]

Knill, D. C., Maloney, L. T. & Trommershäuser, J. (2007), Sensorimotor processing and goal-directed movement. Journal of Vision, 7(5):i, 1-2. [article]

Dean, M., Wu, S.-W. & Maloney, L. T. (2007), Trading off speed and accuracy in rapid, goal directed movements, Journal of Vision, 7(5):10, 1-12. [article]

Ho, Y.-X., Maloney, L. T. & Landy, M. S. (2007), The effect of viewpoint on perceived visual roughness, Journal of Vision, 7, 1-16. [article]

Rhodes, G., Maloney, L. T., Turner, J. & Ewing, L. (2007), Adaptive face coding and discrimination around the average face, Vision Research, 47, 974-989. [pdf]

Ho, Y.-X., Maloney, L. T. & Landy, M. S. (2007), The effect of viewpoint on perceived visual roughness, Journal of Vision, 1,1-16 [article]

Maloney, L. T., Trommershäuser, J. & Landy, M. S. (2007), Questions without words: A comparison between decision making under risk and movement planning under risk. In Gray, W. (Ed), Integrated Models of Cognitive Systems. New York , NY : Oxford University Press, pp. 297-313 [pdf]

2006

Dal Martello, M.F. & Maloney, L.T. (2006), Where are kin recognition signals in the human face?, Journal of Vision 6, 1356-1366. [article]

Schultz, S., Doerschner, K., & Maloney, L. T. (2006), Color constancy and hue scaling. Journal of Vision, 6, 1102-1116. [pdf] [article]

Maloney, L. T. & Dal Martello, M. F. (2006), Kin recognition and the perceived facial similarity of children. Journal of Vision, 6, 1047-1056 [article]

Trommershäuser, J., Landy, M. S. & Maloney, L. T. (2006), Humans rapidly estimate expected gain in movement planning. Psychological Science, 11, 981-988. [pdf]

Fulvio, J. M., Singh, M. & Maloney, L. T. (2006), Combining achromatic and chromatic cues to transparency, Journal of Vision, 6, 760-776. [article]

Trommershäuser, J., Mattis, J., Landy, M. S. & Maloney, L. T. (2006), Limits to human movement planning with delayed and unpredictable onset of needed information. Experimental Brain Research, 275, 276-284. [pdf]

Boyaci, H., Doerschner, K., Snyder, J. L. & Maloney, L. T. (2006), Surface color perception in three-dimensional scenes. Visual Neuroscience, 23, 311-321 [pdf]

Ho, Y.-X., Landy, M. S. & Maloney, L. T. (2006), How illuminant direction affects perceived visual roughness, Journal of Vision, 6, 634-648 [article]

Wu, S.-W., Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2006), Limits to human movement planning in tasks with asymmetric gain landscapes. Journal of Vision, 6, 53-63. [article]

Logvinenko, A. D. & Maloney, L. T. (2006), The proximity structure of achromatic surface colors and the impossibility of asymmetric lightness matching. Perception & Psychophysics, 68. 76-83. [pdf].

Boyaci, H., Doerschner, K. & Maloney, L. T. (2006), Cues to an equivalent lighting model, Journal of Vision,6, 106-118 [article]

Fulvio, J. M., Singh, M. & Maloney, L. T. (2006), Consistency of location and gradient judgments of visually-interpolated contours. Computer Vision and Pattern Recognition, Proceedings '06, in press, 4/06 .[pdf]

2004-2005

Maloney, L. T., Dal Martello, M. F., Sahm, C. & Spillmann, L. (2005), Past trials influence perception of ambiguous motion quartets through pattern completion. Proceedings of the National Academy of Sciences, 102, 3164-3169. [pdf]

Trommershäuser, J., Gepshtein, S., Maloney, L. T., Landy, M. S. & Banks, M. S. (2005), Compensation for changes in effective movement variability. Journal of Neuroscience, 25, 7169-7178. [pdf]

Snyder, J. L., Doerschner, K., & Maloney, L. T . (2005), Illumination estimation in three-dimensional scenes with and without specular cues, Journal of Vision, 5, 863-877. [article]

Graf, E. W., Warren, P. A. & Maloney, L. T . (2005), Explicit estimation of visual uncertainty in human motion processing. Vision Research, 45, 3050-3059. [pdf]

Wolfe, U., Maloney, L. T. & Tam, M. (2005), Distortions of perceived length in the fronto-parallel plane: Tests of perspective theories, Perception & Psychophysics, 67, 967-979. [pdf]

Maloney, L. T., Boyaci, H. & Doerschner, K. (2005), Surface color perception as an inverse problem in biological vision. Proceedings of the SPIE - IS & T Electronic Imaging, 5674, 15-26. [pdf]

Boyaci, H., Doerschner, K. & Maloney, L. T. (2004), Perceived surface color in binocularly-viewed scenes with two light sources differing in chromaticity. Journal of Vision, 4, 664-679 [article]

Warren, P.E. Maloney, L. T. & Landy, M. S. (2004), Interpolating sampled contours in 3D: Perturbation analyses. Vision Research, 44, 815-832 [pdf].

Doerschner, K., Boyaci, H. & Maloney, L. T. (2004), Human observers compensate for secondary illumination originating in nearby chromatic surfaces, Journal of Vision, 4, 92-105[article]

Brainard. D. H. & Maloney, L. T. (2004), Perception of color and material properties in complex scenes, Journal of Vision, 44, 2-4. [article]

2002-2003

Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2003), The consistency of bisection judgments in visual grasp space. Journal of Vision , 3, 795-807 [article]

Maloney, L. T. & Yang, J. N. (2003), Maximum likelihood difference scaling. Journal of Vision, 3, 573-585. [article]

Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2003), Statistical decision theory and tradeoffs in motor response. Spatial Vision, 16, 255-275. [pdf]

Boyaci, H., Maloney, L. T. & Hersh, S. (2003), The effect of perceived surface orientation on perceived surface albedo in three-dimensional scenes, Journal of Vision, 3, 541-553. [article]

Oruç, I, Maloney, L. T., & Landy, M. S. (2003), Weighted linear cue combination with possibly correlated error, Vision Research, 43, 2451-2468. [pdf]

Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2003), Statistical decision theory and rapid, goal-directed movements. Journal of the Optical Society A, 1419-1433. [pdf]

Maloney, L. T. & Yang, J. N. (2003), The illumination estimation hypothesis and surface color perception. Mausfeld, R., & Heyer, D. [Eds], Colour: Connecting the Mind to the Physical World. Oxford: Oxford University Press, pp. 335-358.

Maloney, L. T. (2003), Surface color perception in constrained environments. In Mausfeld, R., & Heyer, D. [Eds], Colour: Connecting the Mind to the Physical World. Oxford: Oxford University Press, pp. 279-299.

Maloney, L. T. (2003). Statistical decision theory and evolution [research focus]. Trends in Cognitive Science, 7, 473-475. [pdf]

Maloney, L. T. (2003), Surface color perception in constrained environments [Commentary]. Behavioral & Brain Sciences, 26, 38-39.

Maloney, L. T. (2002), Illuminant estimation as cue combination. Journal of Vision, 2, 493-504.[article]

Warren, P. E., Maloney, L. T., & Landy, M. S. (2002), Interpolating sampled contours in 3D: Analyses of variability and bias. Vision Research, 42, 2431-2446. [pdf]

Maloney, L. T. (2002), Statistical decision theory and biological vision. In Heyer, D. & Mausfeld, R. [Eds], Perception and the Physical World: Psychological and Philosophical Issues in Perception.. New York: Wiley, pp. 145-189. [pdf]

Mamassian, P., Landy, M. S., & Maloney, L. T. (2002), Bayesian modeling of visual perception. In Rao, R., Lewicki, M., & Olshausen, B. [Eds], Probabilistic Models of the Brain; Perception and Neural Function. Cambridge, MA: MIT Press, 13-36. [pdf]

Maloney, L. T. & Schirillo, J. A. (2002), Color constancy, lightness constancy, and the articulation hypothesis. Perception, 31, 135-139.

Maloney, L. T. (2002), A Review of D. M. Regan, Human Perception of Objects; Early Visual Processing of Spatial Form Defined by Luminance, Color, Texture, Motion and Binocular Disparity. Perception, 31, 1031-1032.

Maloney, L. T., Mausfeld, R. & Heyer, D. (2002), Introduction to the special issue on the work of Roger Shepard: The case for cognitive universals, Behavioral & Brain Sciences, 579-580.

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Review Chapters and Articles

Brainard, D. H. & Maloney, L. T. (2011), Surface color perception and equivalent illumination models.  Journal of Vision, 11(5):1, 1–18. [article]

Maloney, L. T., Gerhard, H. E., Boyaci, H. & Doerschner, K. (2011), Surface color perception and light field estimation in 3D scenes.  In Harris, L. R. & Jenkin, M. R. M. [Eds], Vision in 3D environments.  Cambridge, UK: Cambridge University Press,pp. 280-307. [pdf]

Maloney, L. T. & Zhang, H. (2010), Decision-theoretic models of visual perception and action. Vision Research, 50, 2362-2374. [pdf]

Trommershäuser, J., Maloney, L. T. & Landy M. S. (2008), Decision making, movement planning and statistical decision theory. . Trends in Cognitive Science, in press, 4/2008. [pdf]

Trommershäuser, J., Maloney, L. T. & Landy M. S. (2008), The expected utility of movement. In Glimcher, P., Camerer, C., Fehr, E & Poldrack, R. (Eds), Neuroeconomics, 10/2007. [pdf]

Boyaci, H., Doerschner, K., Snyder, J. L. & Maloney, L. T. (2006), Surface color perception in three-dimensional scenes. Visual Neuroscience, 23, 311-321 [pdf]

Maloney, L. T., Trommershäuser, J. & Landy, M. S. (2006), Questions without words: A comparison between decision making under risk and movement planning under risk. In Gray, W. (Ed), Integrated Models of Cognitive Systems. New York , NY : Oxford University Press, in press, 9/2005. [pdf]

Maloney, L. T., Boyaci, H. & Doerschner, K. (2005), Surface color perception as an inverse problem in biological vision. Proceedings of the SPIE - IS & T Electronic Imaging, 5674, 15-26. [pdf]

Maloney, L. T. (2002), Statistical decision theory and biological vision. In Heyer, D. & Mausfeld, R. [Eds], Perception and the Physical World: Psychological and Philosophical Issues in Perception. New York: Wiley, pp. 145-189. [pdf]

Maloney, L. T. (1999), Physics-based approaches to modeling surface color perception. In Gegenfurtner, K. R., & Sharpe, L. T. [Eds] (1999), Color Vision: From Genes to Perception. Cambridge, UK: Cambridge University Press, pp. 387-422. [pdf]

Maloney, L. T. (1996), Exploratory vision: Some implications for retinal sampling and reconstruction. In Landy, M. S., Maloney, L. T., and Pavel, M. [Eds.], Exploratory Vision: The Active Eye. New York: Springer-Verlag, 121-156.

Landy, M. S., Maloney, L. T., Johnston, E. B., & Young, M. (1995), Measurement and modeling of depth cue combination: In defense of weak fusion. Vision Research, 35, 389-412. [pdf]

Maloney, L. T. (1993), Color constancy and color perception: the linear models framework. In Meyer, D. E., and Kornblum, S. [Eds], Attention & Performance XIV: Synergies in Experimental Psychology, Artificial Intelligence, and Cognitive Neuroscience -- A Silver Jubilee. Cambridge, Massachusetts: MIT Press, 59-78.

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Surface Color in 3D scenes

Researchers studying surface color perception have typically used stimuli that consist of a small number of matte patches (real or simulated) embedded in a plane perpendicular to the line of sight (a 'Mondrian', named after the Dutch artist Piet Mondrian). Reliable estimation of surface properties analogous to color is a difficult if not impossible computational problem in such limited scenes (Maloney, 1999). In more realistic, three-dimensional scenes the problem is difficult but not intractable, in part because considerable information about the spatial and spectral distribution of the illumination is usually available in the form of cues to the illuminant. We are engaged in a series of experiments that examine whether the human visual system discounts the spatial and spectral distribution of the illumination in judging matte surface lightness and color and what illuminant cues the visual system uses in estimating the flow of light in a scene.

The stimulus above is a binocular pair, with the right eye image repeated in the order Right-Left-Right. You can fuse the two images on the left with eyes crossed ('crossed fusion') or the two images on the right with eyes uncrossed ('uncrossed fusion'). The scene is taken from a recent experiment where we examine perception of color in computer-generated scenes with two yellow punctate sources ('suns') and a blue diffuse sky. The punctate sources are behind the observer, not directly visible. The observer's task is to set the central rectangular patch to be neither blue nor yellow and neither red nor green (i.e. grey, neutral, colorless). This task is called an achromatic matching task. It allows us to assess whether the observer can work out how the light sources in the scene are arranged and successfully perceive stable surface colors in simulated environments with two suns in the sky (yes, they can do it!).

Kitazaki, M., Kobiki, H. & Maloney, L.T. (2008), The effect of pictorial depth cues, binocular disparity and motion parallax depth cues on lightness perception in three-dimensional virtual scenes, PLoS ONE, 3(9): e3177, 1-9. [pdf]

Doerschner, K., Boyaci, H.
& Maloney, L. T. (2007), Testing limits on matte surface color perception in three-dimensional scenes with complex light fields, Vision Research, 47, 3409-3423 [pdf]

Schultz, S., Doerschner, K., & Maloney, L.T. (2006), Color Constancy and hue scaling. Journal of Vision, 6, 1102-116. [article]

Boyaci, H., Doerschner, K., Snyder, J. L. & Maloney, L. T. (2006), Surface color perception in three-dimensional scenes. Visual Neuroscience, 23, 311-321 [pdf]

Boyaci, H., Doerschner, K. & Maloney, L. T. (2006), Cues to an equivalent lighting model, Journal of Vision, 6, 106-118 [article]

Snyder, J. L., Doerschner, K., & Maloney, L. T. (2005), Illumination estimation in three-dimensional scenes with and without specular cues, Journal of Vision, 5, 863-877.[article]

Maloney, L. T., Boyaci, H. & Doerschner, K. (2005), Surface color perception as an inverse problem in biological vision. Proceedings of the SPIE - IS & T Electronic Imaging, 5674, 15-26. [pdf]

Boyaci, H., Doerschner, K. & Maloney, L. T. (2004), Perceived surface color in binocularly-viewed scenes with two light sources differing in chromaticity. Journal of Vision,4, 664-679 [article].

Doerschner, K., Boyaci, H. & Maloney, L. T. (2004), Human observers compensate for secondary illumination originating in nearby chromatic surfaces, Journal of Vision, 4, 92-105 [article].

Boyaci, H., Maloney, L. T. & Hersh, S. (2003), The effect of perceived surface orientation on perceived surface albedo in binocularly viewed scenes, Journal of Vision, 3, 541-553. [article]

Yang, J. N. & Maloney, L. T. (2001), Illuminant cues in surface color perception: Tests of three candidate cues. Vision Research, 41, 2581-2600. [pdf]

Maloney, L. T. (2002), Illuminant estimation as cue combination. Journal of Vision, 2, 493-504. [article]

Maloney, L. T. & Yang, J. N. (2003), The illumination estimation hypothesis and surface color perception. Mausfeld, R., & Heyer, D. [Eds], Colour: Connecting the Mind to the Physical World. Oxford: Oxford University Press, pp. 335-358.

Maloney, L. T. (2003), Surface color perception and environmental constraints. In Mausfeld, R., & Heyer, D. [Eds], Colour: Connecting the Mind to the Physical World. Oxford: Oxford University Press, pp. 279-299.

Maloney, L. T. (1999), Physics-based approaches to modeling surface color perception. In Gegenfurtner, K. R., & Sharpe, L. T. [Eds] (1999), Color Vision: From Genes to Perception. Cambridge, UK : Cambridge University Press, pp. 387-422. [pdf]
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Movement Planning under Risk

We are investigating speeded movement tasks that are equivalent to decision making under risk. In these tasks subjects attempt to touch reward regions on a display screen and avoid nearby penalty regions, much as a golfer aims to reach the green while avoiding nearby sand traps. The subject is required to complete the movement within a short time and, like the golfer, cannot completely control the outcome of the action. We are interested in whether the subject takes his or her own movement uncertainty into account in planning movements. We record subjects' hand and arm movements in three dimensions with an Optotrak 3020 motion tracking device or a Polhemus HST-16 electromagnetic tracker. These tasks form a promising alternative domain in which to study decision making and they are distinguished by the fact that the uncertainties surrounding possible outcomes are intrinsic to the motor system.

The papers by Trommershäuser, Maloney & Landy (2003) report our first attempts while the review chapter by Maloney, Trommershäuser & Landy (2006) focuses on connections to decision making. We are actively investigating how the motor system compensates for its own uncertainty in planning movements as well as studying decision making in a new modality.

In ongoing experiments, we are also looking at how information flows from the visual system to the motor system and how flexible motor planning can be in a rapidly changing environment. We are also looking at how partial information (encoded as a statistical prior distribution) influences movement planning and how rapidly the motor system recovers when we restrict its freedom of movement. We hope that this last series of experiments will tell us more about recovery from stroke and injury.

Hudson, T. E., Maloney, L. T. & Landy, M. S. (2008), Optimal compensation for temporal uncertainty in movement planning. PLoS Computational Biology, 4(7):e100130, 1-9. [pdf]

Trommershäuser, J., Maloney, L. T. & Landy M. S. (2008), Decision making, movement planning and statistical decision theory. . Trends in Cognitive Science, 12(8), 291-297 [pdf]

Trommershäuser, J., Maloney, L. T. & Landy M. S. (2008), The expected utility of movement. In Glimcher, P., Camerer, C., Fehr, E & Poldrack, R. (Eds), Neuroeconomics, New York: Academic Press, pp. 95-111. [pdf]

Hudson, T. E., Maloney, L. T. & Landy, M. S. (2007), Movement planning with probabilistic target information. Journal of Neurophysiology, 98, 3034-3046. [pdf]

Knill, D. C., Maloney, L. T. & Trommershäuser, J. (2007), Sensorimotor processing and goal-directed movement. Journal of Vision, 7(5):i, 1-2. [article]

Dean, M.
, Wu, S.-W. & Maloney, L. T. (2007), Trading off speed and accuracy in rapid, goal directed movements, Journal of Vision, 7(5):10, 1-12. [article]

Trommershäuser, J., Landy, M. S. & Maloney, L. T. (2006), Humans rapidly estimate expected gain in movement planning. Psychological Science, 11, 981-988 [pdf]

Wu, S.-W., Trommershäuser, J., Maloney, L.T. & Landy, M.S. (2006), Limits to human movement planning in tasks with asymmetric gain landscapes. Journal of Vision, 6, 53-63. [article]

Trommershäuser, J., Mattis, J., Landy, M. S. & Maloney, L. T. (2006), Limits to human movement planning with delayed and unpredictable onset of needed information. Experimental Brain Research, 175, 276-284. [pdf]

Trommershäuser, J., Gepshtein, S., Maloney, L. T., Landy, M. S. & Banks, M. S. (2005), Compensation for changes in effective movement variability. Journal of Neuroscience, 25, 7169-7178. [pdf]

Maloney, L. T., Trommershäuser, J. & Landy, M. S. (2006), Questions without words: A comparison between decision making under risk and movement planning under risk. In Gray, W. (Ed), Integrated Models of Cognitive Systems. New York , NY : Oxford University Press, pp. 297-313 [pdf]

Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2003), Statistical decision theory and rapid, goal-directed movements. Journal of the Optical Society A, 1419-1433. [pdf]

Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2003), Statistical decision theory and tradeoffs in motor response. Spatial Vision, 16, 255-275. [pdf]

Maloney, L. T. (2002), Statistical decision theory and biological vision. In Heyer, D. & Mausfeld, R. [Eds], Perception and the Physical World: Psychological and Philosophical Issues in Perception. New York: Wiley, pp. 145-189. [pdf]

Mamassian, P., Landy, M. S., & Maloney, L. T. (2002), Bayesian modeling of visual perception. In Rao, R., Lewicki, M., & Olshausen, B. [Eds], Probabilistic Models of the Brain; Perception and Neural Function. Cambridge, MA: MIT Press, 13-36. [pdf]

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Material Perception

We are studying how human observers estimate surface properties such as roughness, glossiness, transparency, and refractive index.

In Ho, Landy and Maloney (2006, in press), we examined visual estimation of surface roughness using random computer-generated three-dimensional (3D) surfaces rendered under a mixture of diffuse lighting and a punctate source. You can see some examples below. The surfaces increase in physical roughness from left to right. The different rows correspond to different lighting conditions.

We estimated how perceived roughness varied with the direction of illumination. A 'roughness constant' observer would make estimates of surface roughness that did not vary at all with changes in illumination direction and we assessed how close human observers came to this ideal. The angle between the tangent to the plane containing the surface texture and the direction to the punctate source was varied from 50 to 70 degrees across lighting conditions. Observers were presented with pairs of surfaces under different lighting conditions and indicated which 3D surface appeared rougher.

All observers perceived surfaces to be markedly rougher with decreasing illuminant angle (going from the bottom to the top row above). We identified four novel cues that are valid cues to roughness under any single lighting condition but that are not invariant under changes in lighting condition. We modeled observers' deviations from roughness constancy as a weighted linear combination of these 'pseudo-cues' and found that they account for a substantial amount of observers' systematic deviations from roughness constancy with changes in lighting condition.

These novel cues are not valid cues to roughness when lighting changes. The surfaces outlined in red in the figure above all have the same physical roughness but different degrees of shadows, etc. However, these same cues would be valid cues to roughness within a single lighting condition (blue rectangle). Consequently, these pseudo-cues may be the result of cue learning in one context (illumination invariant) incorrectly generalized to a different context (illumination changing). With Yun-Xian Ho and Michael Landy.

In another study (Fulvio, Singh, Maloney, 2006), we investigated how achromatic and chromatic cues interact to produce transparency. Observers were shown six-region stimulus displays (shown above) that either varied in lightness (left) or color (right). They made adjustments of the color and luminance attributes of one of the filter regions to achieve the best percept of transparency. The Metelli-D'Zmura conditions for transparency are diagrammed in the center above. However, we were interested primarily not in the mean settings made bit in setting reliability, the reciprocal of setting variance. We wished to determine whether the combination of chromatic and achromatic information leads to enhanced reliability of perceived transparency. We compared their settings in luminance only conditions (above left) and color only conditions (above right) C to their color settings when we superimposed the two patterns.. Color adjustments were more reliable when accompanied by luminance information, but surprisingly not vice versa. With Jacqueline Fulvio and Manish Singh.

Recently, we started looking at perceptual scaling of refractive index of transparent materials (how much the material bends light passing through it). Show above are two 'pebbles' of the same thickness but different refractive indices. The one on the right probably looks a bit 'plumper' but the only difference between the pebbles is in refractive index. We are using a method called Maximum Likelihood Difference Scaling to study how human observers perceive the refractive index of transparent material (with Roland Fleming and Frank Jäkel; images by Roland Fleming).

Ho, Y.-H., Landy. M. S. & Maloney, L. T. (2008), Conjoint measurement of gloss and surface texture. Psychological Science, 19(2), 196-204. [pdf]

Ho, Y.-X.,
Maloney, L. T. & Landy, M. S. (2007), The effect ofw viewpoint on perceived visual roughness, Journal of Vision, 7, 1-16. [article]

Ho, Y.-X., Landy, M. S. & Maloney, L. T. (2006), How illuminant direction affects perceived visual roughness, Journal of Vision, 6, 634-648 [article]

Fulvio, J. M., Singh, M. & Maloney, L. T. (2006), Combining achromatic and chromatic cues to transparency, Journal of Vision, in press, 3/2006. [pdf]

Brainard. D. H. & Maloney, L. T. (2004), Perception of color and material properties in complex scenes, Journal of Vision, 44, 2-4. [article]

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Statistical Models of Visual Judgements

Human observers can have multiple sources of information about the shape, location, orientation, color or material of objects in a scene and each source is typically perturbed by error. Combining these sources of information into a single estimate is a fundamental problem in statistics. In our work, we compare human performance in combining information for multiple sources to optimal performance. We have investigated cue combination in human perception of depth, shape, slant and color.

In one recent experiment (Oruç, Maloney & Landy, 2003), we asked observers to repeatedly adjust the slant of a plane to 75 deg. Feedback was provided after each setting and the observers trained extensively until their setting error stabilized. We designed the experiment so that we could determine whether the observer's estimates of slant from each of two slant cues were correlated or uncorrelated.

The slant of the plane was defined by either linear perspective alone (a grid of lines) or texture gradient alone (diamond-shaped texture elements) or the two cues together. We chose a HIGH and LOW variance version of each cue type and measured setting variability in four single-cue conditions (LOW, HIGH for each cue) and in the four possible combined-cue conditions (LOW-LOW, LOW-HIGH, etc.).

We compared performance in the combined-cue conditions to predictions based on single-cue performance. Six out of eight observers did better with combined cues than with either cue alone, showing that they were in fact combining information from both cues. For three observers, performance was consistent with optimal combination of uncorrelated cues. Three other observers' results were also consistent with optimal combination, but with the assumption that internal cue estimates were correlated. The remaining two observers' performances were sub-optimal.

Knoblauch, K. & Maloney, L. T. (2008), MLDS: Maximum likelihood difference scaling in R. Journal of Statistical Software, 25(2), 1-26 [pdf]

Charrier, C.
, Maloney, L. T., Cherifi, H. & Knoblauch, K., (2007), Maximum likelihood difference scaling of image quality in compression-degraded images. Journal of the Optical Society of America A, 24, 3814-3826 [pdf]

Dal Martello, M. F. & Maloney, L. T. (2006), Where are kin recognition signals in the human face?, Journal of Vision, 6, 1356-1366. [article]

Boyaci, H., Doerschner, K. & Maloney, L. T. (2006), Cues to an equivalent lighting model, Journal of Vision, 6,106-118 [article]

Graf, E. W., Warren, P. A. & Maloney, L. T. (2005), Explicit estimation of visual uncertainty in human motion processing. Vision Research, in press, 8/2005. [pdf]

Maloney, L. T., Dal Martello, M. F., Sahm, C. & Spillmann, L. (2005), Past trials influence perception of ambiguous motion quartets through pattern completion. Proceedings of the National Academy of Sciences,102, 3164-3169. [pdf]

Warren, P.E., Maloney, L. T. & Landy, M. S. (2004), Interpolating sampled contours in 3D: Perturbation analyses. Vision Research, 44, 815-832 [pdf].

Oruç, I, Maloney, L. T., & Landy, M. S. (2003), Weighted linear cue combination with possibly correlated error, Vision Research, 43, 2451-2468. [pdf]

Yang, J. N. & Maloney, L. T. (2001), Illuminant cues in surface color perception: Tests of three candidate cues. Vision Research, 41, 2581-2600. [pdf]

Maloney, L. T. (2002), Illuminant estimation as cue combination. Journal of Vision, 2, 493-504. [pdf]

Warren, P. E., Maloney, L. T., & Landy, M. S. (2002), Interpolating sampled contours in 3D: Analyses of variability and bias. Vision Research, 42, 2431-2446. [pdf]

Maloney, L. T. (2002), Statistical decision theory and biological vision. In Heyer, D. & Mausfeld, R. [Eds], Perception and the Physical World: Psychological and Philosophical Issues in Perception. New York: Wiley, pp. 145-189. [pdf]

Maloney, L. T. (1999), Physics-based approaches to modeling surface color perception. In Gegenfurtner, K. R., & Sharpe, L. T. [Eds] (1999), Color Vision: From Genes to Perception. Cambridge, UK : Cambridge University Press, pp. 387-422. [pdf]

Maloney, L. T. (1996), Exploratory vision: Some implications for retinal sampling and reconstruction. In Landy, M. S., Maloney, L. T., and Pavel, M. [Eds.], Exploratory Vision: The Active Eye. New York: Springer-Verlag, 121-156.

Landy, M. S., Maloney, L. T., Johnston, E. B., & Young, M. (1995), Measurement and modeling of depth cue combination: In defense of weak fusion. Vision Research, 35, 389-412. [pdf]

Young, M. J., Landy, M. S. & Maloney, L. T. (1993), A perturbation analysis of depth perception from combinations of texture and motion cues. Vision Research, 33, 2685-2696. [pdf]

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Geometrical Models of Visual Judgments

The papers below describe experiments where subjects were asked to perform geometric judgments in binocular space, color space or face space. We are interested in how observers represent space, color and complex stimuli and what kinds of judgments they can perform on these representations. Our goal is to better understand the 'machinery of the brain.'

The figure below, taken from Trommershäuser, Maloney & Landy (2003) comes form a series of experiments examining geometric judgments in near binocular space where hand and eye typically work together. Our goal in doing this experiment was to see whether the visual system's judgments of bisection and collinearity were accurate in this 'visual grasp space'.

The figure shows the outcome of one observer's bisection setting (red dot) when she was asked to set the point that bisected the intervals joining two other points that are not shown in the diagram because, at this scale, they would be very far away. We found that observers' settings in visual grasp space are typically inconsistent with any simple geometry,and that observers differ from one another in no patterned way. Although each observer saw an idiosyncratic, distorted picture of the world, the observer's perception of collinearity and bisection was roughly invariant under small eye movements.

We are also engaged in studying super-threshold color differences ('color proximity') and the geometry of color space using newly developed scaling methods. See for example, Logvinenko & Maloney (2006) or Wuerger, Maloney & Krauskopf, (1995).

Tokunaga, R., Logvinenko, A. D. & Maloney, L. T. (2008), Multidimensional scaling of dissimilarities between yellow-blue surfaces rated under neutral light sources. Visual Neuroscience, 25, 395-398 [pdf]

Logvinenko, A., Petrini, K. & Maloney, L. T. (2008), A scaling analysis of the snake lightness illusion. Perception & Psychophysics, 70(5), 828-840 [pdf]

Schultz, S., Doerschner, K., & Maloney, L. T. (2006), Color constancy and hue scaling. Journal of Vision, 6, 1102-1116. [article]

Fulvio, J. M., Singh, M. & Maloney, L. T. (2006), Consistency of location and gradient judgments of visually-interpolated contours. Computer Vision and Pattern Recognition, Proceedings '06, in press, 4/06 .[pdf]

Logvinenko, A. D. & Maloney, L. T. (2006), The proximity structure of achromatic surface colors and the impossibility of asymmetric lightness matching. Perception & Psychophysics, 68. 76-83. [pdf].

Wolfe, U., Maloney, L. T. & Tam, M. (2005), Distortions of perceived length in the fronto-parallel plane: Tests of perspective theories, Perception & Psychophysics, 67, 967-979. [pdf]

Trommershäuser, J., Maloney, L. T. & Landy, M. S. (2003), The consistency of bisection judgments in visual grasp space. Journal of Vision, 3, 795-807. [article]

Warren, P.E., Maloney, L. T. & Landy, M. S. (2004), Interpolating sampled contours in 3D: Perturbation analyses. Vision Research, 44, 815-832 [pdf].

Warren, P. E., Maloney, L. T., & Landy, M. S. (2002), Interpolating sampled contours in 3D: Analyses of variability and bias. Vision Research, 42, 2431-2446 [pdf].

Maloney, L. T. (1996), Exploratory vision: Some implications for retinal sampling and reconstruction. In Landy, M. S., Maloney, L. T., and Pavel, M. [Eds.], Exploratory Vision: The Active Eye. New York: Springer-Verlag, 121-156.

Maloney, L. T., Wuerger, S. M. & Krauskopf, J. (1995), A method for testing Euclidean representations of proximity judgments in linear psychological spaces. In Luce, R. D., D'Zmura, M., Hoffman, D., Iverson, G. J. & Romney, A. K. [Eds], Geometric Representations of Perceptual Phenomena; Papers in Honor of Tarow Indow on his 70th Birthday. Mahwah , NJ : Erlbaum.

Wuerger, S. M., Maloney, L. T., & Krauskopf, J. (1995), Proximity judgments in color space: Tests of a Euclidean color geometry. Vision Research, 35, 827-835. [pdf]

Hon, A. K., Maloney, L. T., & Landy, M. S. (1997), The influence function for visual interpolation. In Rogowitz, B. E. & Pappas, T. N. [Eds], Human Vision and Electronic Imaging II; Proceedings of the SPIE, 3016, 409-419. [pdf]

Maloney, L. T., and Ahumada, A. J. (1989), Learning by assertion: A method for calibrating a simple visual system. Neural Computation, 1, 387-395.

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Face Perception

An individual's face is a rich source of information about the gender, age, health and identity of the individual. As an extension to our work on cue combination, we are examining what facial information human observers can abstract about genetic relatedness: specifically how well can they judge whether pairs of children are siblings?

The pictures below on the left portray the four children of Charles Marsham, First Earl of Romney (The Marsham Children by Thomas Gainsborough, 1787 Staatliche Museen, Berlin, Photo credit: Bildarchiv Preussicher Kulturbesitz / Art Resource, NY). While we use photos of children in our studies, the evident similarities and differences in the Marsham children's faces give an idea of the complexity of the task of judging kinship from faces.

In Maloney & Dal Martello (2006), we examine the connection between a hypothetical kin recognition signal available in visual perception and the perceived facial similarity of children. One group of observers rated the facial similarity of pairs of children portrayed in photographs. Half of the pairs were siblings but the observers were not told this. A second group classified the pairs as siblings or non-siblings. An optimal Bayesian classifier, given the similarity ratings of the first group, was as accurate in judging siblings as the second group. Mean rated similarity (above right) was also an accurate linear predictor (R 2 = 0.96) of the log-odds that the rated pair portrayed were, in fact, siblings. Surprisingly, mean rated similarity did not vary with the age difference or gender difference of the pairs, both of which were counterbalanced across the stimuli. We conclude that the perceived facial similarity of children is little more than a graded kin recognition signal and that this kin recognition signal is effectively an estimate of the probability that two children are close genetic relatives. With Felicita Dal Martello.

In a second study (Dal Martello & Maloney, in press), we report two experiments intended to determine where in the face the cues signalling kinship fall. In both experiments, participants were shown thirty pairs of photographs of children's faces. Half of the pairs portrayed siblings and half did not. The 220 participants were asked to judge whether each pair of photos portrayed siblings. We measured the effect on kin recognition performance of masks that covered the upper half of the face or the lower half (Experiment 1) and the eye region or the mouth region (Experiment 2). Examples of the stimuli for Experiment 1 are shown above (yes, they are siblings). In Experiment 1 we found that the signal detection estimate of performance decreased only 5.3% (n.s.) when the lower face was masked but by more than 65% when the upper face was masked. We tested whether combination of kinship information from the two halves of the face can be treated as optimal combination of independent cues and found that it could be. In Experiment 2, we found that masking the eye region led to only a 20% reduction (n.s.) in performance while masking the mouth region led to a non-significant increase in performance. We also found that the eye region contains only slightly more information about kinship than the upper half of the face outside of the eye region.

We are engaged in further studies concerning the localization of kinship and other sources of information within the face and testing how faces are encoded. With Felicita Dal Martello.

Rhodes, G., Maloney, L.T., Turner, J. & Ewing, L. (2007), Adaptive face coding and discrimination around the average face, Vision Research, 47, 974-989 [pdf]

Dal Martello, M. F. & Maloney, L. T. (2006), Where are kin recognition signals in the human face?, Journal of Vision, 6, 1356-1366. [article]

Maloney, L. T. & Dal Martello, M. F. (2006), Kin recognition and the perceived facial similarity of children. Journal of Vision, 6, 1047-1056 [article]

Address


Laurence T. Maloney
Professor of Psychology and Neural Science
Department of Psychology
Center for Neural Science
6 Washington Place, 8th Floor
New York, NY 10003

Office Phone:

+1 212 998-7851

Perception Lab:

+1 212 998-7853

Email: laurence.maloney@nyu.edu
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Updated